15 results about "Motor symptoms" patented technology

The invention relates to a Parkinson's disease motion symptom auxiliary diagnosis system based on multi-modal artificial intelligence, and belongs to the field of medical AI auxiliary diagnosis. The system integrates multi-modal image data, and realizes common symptom classification and severity degree scoring of four motion symptoms of Parkinson's disease through preprocessing, multi-modal feature extraction combined with a 3D CNN branch and a Vision Transform branch, causal feature screening based on an IAMB algorithm, and a multi-modal fusion and multi-task learning module. The system can effectively fuse structure and functional image information, improves diagnosis accuracy and interpretability, is especially suitable for early symptom identification and quantitative evaluation, and has high clinical practical value.

The invention relates to a novel compound as a 5-HT2A receptor inverse agonist, and a preparation method and a pharmaceutical composition thereof. The invention also relates to application of the compound or the pharmaceutical composition in preparation of drugs for treating 5-HT2A receptor related diseases, wherein the diseases comprise non-motor symptoms caused by Parkinson's disease, such as delusional disorder, hallusion, depression, anxiety, cognitive disorder and sleep disorder; dementia-related mental disorders; major depression; or negative symptoms of schizophrenia and the like.

To provide a system and method for the digital graphic measurement of Parkinson's disease. [Solution] A system and method for digital graphic measurement of Parkinson's disease according to an embodiment of the present invention are illustrated. One embodiment includes a digital graphic measurement device comprising a housing, a plurality of keys mounted on the housing, a plurality of sensors, the sensors in the plurality of sensors being associated with the keys in the plurality of keys and capable of measuring the amplitude of key presses, and an input / output interface within the housing, wherein the digital graphic measurement device is configured to transmit key press data generated by the sensors to a controller via the input / output interface, and the key press data is used to generate a plurality of digital graphic indices that describe the motor symptoms of the user of the digital graphic measurement device.

The present disclosure relates to methods and compositions for treating Parkinson's disease, a neurodegenerative disorder characterized by loss of dopaminergic neurons. In particular, the present disclosure provides preparations of dopaminergic cells that have been demonstrated to have therapeutic effects on both motor and non-motor symptoms of the disease.

The purpose of the present invention is to provide: a therapeutic agent or a recurrence preventive agent for serotonergic system- or dopaminergic system-related diseases, in particular, mental dysfunction symptoms and other non-motor symptoms of Parkinson's disease; and a method for treating the aforesaid symptoms or preventing the recurrence of the same. A compound represented by formula (1) [wherein each symbol is as defined in the description] or a pharmaceutically acceptable salt thereof can exhibit an effect of treating serotonergic system- or dopaminergic system-related diseases, in particular, mental dysfunction symptoms and other non-motor symptoms of Parkinson's disease and / or an effect of preventing the recurrence of the same.

The invention provides a system for quantitative evaluation of Parkinson's disease hand motion symptoms, and the system comprises a glove base which is worn on the hand of a patient to be evaluated; the triboelectric sensors are located at finger joints on the back side of the glove base and used for collecting bending signals of the finger joints when the patient executes specified actions; the inertial measurement unit is positioned in a hand back area on the glove base and is used for collecting a movement signal of the whole hand when the patient executes a specified action; the data acquisition and processing unit is used for calculating a tremor evaluation index value and a muscular tension evaluation index value based on the motion signal of the whole hand, and calculating a motion delay evaluation index value based on the bending signal of the finger joint and the motion signal of the whole hand; and inputting the three types of evaluation index values into a pre-constructed mapping relationship between each evaluation index and a clinical score to obtain respective scores, and summing the scores to obtain an overall score. According to the invention, fine actions of the hand of the Parkinson's disease patient can be reflected, and accurate quantitative indexes of hand movement symptoms can be provided.

The invention discloses a Parkinson's disease patient subtype intelligent typing method based on machine learning, and the method comprises the steps: integrating the multi-dimensional data of a patient, including demographic information, motor and non-motor symptoms, iconography and biomarkers, and utilizing a technical means of combining unsupervised learning and supervised learning, and carrying out the subtype intelligent typing of the Parkinson's disease patient. The Parkinson's disease classification method has the advantages that fine layering of Parkinson's disease patients is achieved, the limitation problems of roughness and single dimension of a traditional classification method are solved, disease heterogeneity can be revealed more accurately, and a scientific basis is provided for formulating an individualized treatment strategy; the disease subtypes with different clinical features and prognosis differences are recognized through clustering analysis, then the supervised learning model is used for conducting rapid and accurate subtype classification on new patients, the classification result is integrated into a clinical decision support system, comprehensive and personalized patient management suggestions are provided for doctors, and the life quality of the patients is improved.

This invention proposes an early detection method for Parkinson's disease based on EfficientNetV2-S. Addressing the problems of traditional diagnosis relying on subjective assessment of motor symptoms by doctors, which is prone to misdiagnosis and missed diagnosis in the early stages, this method acquires handwritten images through spiral drawing and waveform handwriting tasks. It then utilizes EfficientNetV2-S to automatically learn subtle jitter features and motion control anomalies in the trajectory. Multi-scale feature fusion enhances the perception of minute local changes, and dual-task joint learning improves the comprehensive discrimination ability across different handwriting tasks. After automatic alignment, size normalization, and data augmentation, the data is input into the model, achieving high-precision, high-efficiency, non-invasive, and easily scalable early screening and assisted diagnosis.

The invention provides a method and a device for generating personalized levodopa prescription recommendation for Parkinson's disease, which are applied to the technical field of artificial intelligence, and the method comprises the following steps: carrying out virtual patient modeling based on patient data to obtain a virtual patient model, the virtual patient model is used for simulating pharmacokinetic behaviors of the levodopa preparation in the body of a patient and generating exercise symptom scores; inputting a preset medication behavior, the exercise symptom score and the patient data into the state transition model to obtain a prediction result of the symptom variation after the target time; and performing multi-stage reinforcement learning based on the patient data, the medication behavior and the prediction result of the symptom variation after the target time through the state transition model to obtain a personalized levodopa prescription strategy, the personalized levodopa prescription strategy being used for outputting levodopa prescription recommendation according to the input patient data. According to the invention, personalized and dynamic levodopa medication guidance can be provided for Parkinson's disease patients.

This invention belongs to the field of pharmaceutical technology, specifically relating to the application of Shouhui Tongbian Capsules in the preparation of drugs for treating Parkinson's disease. Shouhui Tongbian Capsules can significantly improve the damage to dopamine neurons in the substantia nigra and striatum of Parkinson's disease mice with depression induced by MPTP and CUMS, and inhibit the activation of microglia and astrocytes; it not only alleviates the motor symptoms of Parkinson's disease mice, but also significantly improves the non-motor symptoms of Parkinson's disease mice, including mental disorders, and has a significant therapeutic effect on depression caused by Parkinson's disease.

The present disclosure provides a method of treating Dementia with Lewy Bodies (DLB) in a subject, comprising administering to the subject a therapeutically effective amount of a compound of formula Compound I or a pharmaceutically acceptable salt thereof. The method improves cognition, activities of daily living, neuropsychiatric symptoms, and motor symptoms in the subject. The compound may be administered orally for about 6 months or longer, with a total daily dose of about 100 mg to about 300 mg. The method results in improvements in various assessment scales including Montreal Cognitive Assessment Scale (MOCA), Cognitive Drug Research Battery (CDR), Clinician Assessment of Fluctuation (CAF), Alzheimer's Disease Cooperative Study - Activities of Daily Living (ADCS-ADL), Neuropsychiatric Inventory (NPI), and Unified Parkinson's Disease Rating Scale (UPDRS).

Idiopathic Parkinson's disease (iPD) is a multi-system disorder, and the debilitating motor stage of iPD can be preceded for years by a prodromal stage characterized by non-motor symptoms like REM sleep behavior disorder (RBD) and gastrointestinal symptoms. Widespread immune dysregulation has been reported in clinically diagnosed iPD, but the existence of immune deficits during the prodromal stage has yet to be thoroughly investigated. Here, it was shown that multiple stages of iPD, including the pre-motor prodromal stage, can be stratified according to the immuno-metabolic response to stimulation of peripheral blood immune cells ex vivo. Peripheral blood monocytes from RBD patients displayed increased stimulation-dependent secretion of inflammatory cytokines, including TNF, IL-1β, and IL-8, which peaks in the prodromal stage and successively diminishes as PD progresses. Furthermore, T lymphocyte mitochondrial health was correlated with stimulation-evoked cytokine secretion across patients with RBD, early-stage iPD, and moderate-stage iPD. The results disclosed here have broad implications for mechanistic understanding of how peripheral inflammation may drive disease progression, and it reveals novel biomarkers to enable patient stratification and progression monitoring for clinical trials based on immune endophenotypes.

The present application relates to the biomedical technology field, and more particularly to a kind of nano drug preparation and its preparation method and application.The nano drug preparation includes rosmarinic acid and nilotinib, and the mass ratio of rosmarinic acid and nilotinib is 1:0.1-2.The present application provides a kind of composition of rosmarinic acid and nilotinib, which can synergistically activate autophagy, has the effect of neuroprotection and antioxidant stress.The drug loaded with rosmarinic acid and nilotinib provided by the present application can effectively protect dopaminergic neurons in substantia nigra, and then improve the motor symptoms of MPTP-induced PD mice, and provide a prospective scheme for PD targeted therapy.

The present invention relates to methods of treating diseases or disorders that are mediated by the loss of synaptic connectivity and / or plasticity, such as neurological diseases and disorders including obsessive compulsive disorder (OCD), Alzheimer's disease psychosis or psychosis in Alzheimer's disease (AD-P), frontotemporal dementia (FID), behavioral and psychological symptoms in dementia, motor symptoms in Parkinson's disease, and behavioral and psychological symptoms in Parkinson's disease, with (R)-1- (5-methoxy-1H-indol-1-y1)-N,N-dimethylpropan-2-amine (zalsupindole; AAZ-A-154). or a pharmaceutically acceptable salt or solvate thereof.

This invention relates to an odor combination for improving non-motor symptoms of Parkinson's disease. Its active ingredients consist of phenylethanol, eucalyptol, citronellol, and eugenol in a mass ratio of 0.5-2:0.5-2:0.5-2:0.5-2, with menthol microcapsules as the functional adjuvant. Each active ingredient is mixed with the menthol microcapsules in a mass ratio of 2-4:1, and the active ingredients are layered on a hydrogel material. The odor combination can be used alone or in conjunction with a breathing guide to form a multi-layered controlled-release olfactory training component. The odor combination and olfactory training component can generate a more progressive and hierarchical odor stimulation pattern that conforms to the laws of neural information processing, inducing stronger neural plasticity; it can also improve the experience and enjoyment of the training process, thereby increasing the long-term training compliance of Parkinson's disease patients; and the added adjuvant, without interfering with the main olfactory training, helps to regulate the patient's emotions and attention, thus producing a synergistic therapeutic effect.